diff --git a/fast_llm/data/preprocessing/tokenizer.py b/fast_llm/data/preprocessing/tokenizer.py
index 157744f51..bed121af4 100644
--- a/fast_llm/data/preprocessing/tokenizer.py
+++ b/fast_llm/data/preprocessing/tokenizer.py
@@ -32,6 +32,11 @@ class TokenizerConfig(PreprocessingConfig):
         desc="BOS token to use if the tokenizer doesn't define one; must be an existing token.",
         hint=FieldHint.core,
     )
+    allow_no_bos: bool = Field(
+        default=False,
+        desc="Allow the tokenizer to not have a BOS token. Set to True for tokenizers without BOS (e.g. Qwen).",
+        hint=FieldHint.core,
+    )
     max_vocab_size: int | None = Field(
         default=None,
         desc="Constrain output tokens to a specific range. Used for testing.",
@@ -63,8 +68,8 @@ def __init__(self, config: ConfigType):
             self.tokenizer.bos_token = self._config.bos_token
         if self.tokenizer.eos_token_id is None:
             raise ValueError("Tokenizer does not have an EOS token.")
-        if self.tokenizer.bos_token_id is None:
-            raise ValueError("Tokenizer does not have an BOS token.")
+        if self.tokenizer.bos_token_id is None and not self._config.allow_no_bos:
+            raise ValueError("Tokenizer does not have a BOS token. Set allow_no_bos=True to allow this.")
         self.eod_id = self.tokenizer.eos_token_id
         self.bod_id = self.tokenizer.bos_token_id
 
@@ -89,9 +94,9 @@ def tokenize(
         import torch
 
         tokens = self.tokenizer.encode(text, add_special_tokens=False)
-        if begin:
+        if (begin and self.bod_id is not None):
             tokens.insert(0, self.bod_id)
-        if end:
+        if (end and self.eod_id is not None):
             tokens.append(self.eod_id)
 
         if self._config.max_vocab_size is not None:
@@ -271,10 +276,10 @@ def tokenize_chat(
         # Prepend BOS / append EOS if not already present anywhere in the sequence.
         # We check anywhere (not just first/last) because some chat templates add trailing
         # whitespace after the final EOS token, e.g. "<|im_end|>\n".
-        prepend_bos = begin and self.bod_id not in tokens
-        append_eos = end and self.eod_id not in tokens
+        prepend_bos = begin and self.bod_id is not None and self.bod_id not in tokens
+        append_eos = end and self.eod_id is not None and self.eod_id not in tokens
         tokens = [self.bod_id] * prepend_bos + list(tokens) + [self.eod_id] * append_eos
-        train_mask = [False] * prepend_bos + [bool(m) for m in train_mask] + [False] * append_eos
+        train_mask = [False] * prepend_bos + [bool(m) for m in train_mask] + [True] * append_eos
 
         # Convert boolean train mask to loss masking spans (spans where train_mask[i] == False)
         loss_masking_spans = _train_mask_to_loss_spans(train_mask)
diff --git a/tests/data/test_tokenizer.py b/tests/data/test_tokenizer.py
index 4e9e2fdd5..a1b4a0b19 100644
--- a/tests/data/test_tokenizer.py
+++ b/tests/data/test_tokenizer.py
@@ -79,14 +79,14 @@ def test_validate_chat_template_with_markers(common_tokenizer):
     ("messages", "expected_tokens", "expected_loss_masking_spans"),
     (
         # Single turn: full assistant turn (<assistant>Hello</assistant>) is trainable
-        # 15 tokens, trainable indices 7-13, loss mask spans cover 0-6 and 14
+        # 15 tokens, trainable indices 7-14, loss mask spans cover 0-6
         (
             [{"role": "user", "content": "Hi"}, {"role": "assistant", "content": "Hello"}],
             [49152, 27, 789, 29, 16946, 750, 789, 2293, 17822, 29, 7371, 750, 17822, 29, 49152],
-            [(0, 7), (14, 15)],
+            [(0, 7)],
         ),
         # Multi-turn: both assistant turns are fully trainable
-        # 27 tokens, trainable indices 7-13 and 19-25
+        # 27 tokens, trainable indices 7-13 and 19-26
         (
             [
                 {"role": "user", "content": "A"},
@@ -123,10 +123,10 @@ def test_validate_chat_template_with_markers(common_tokenizer):
                 29,
                 49152,
             ],
-            [(0, 7), (14, 19), (26, 27)],
+            [(0, 7), (14, 19)],
         ),
         # System + user + assistant: full assistant turn trainable
-        # 23 tokens, trainable indices 15-21
+        # 23 tokens, trainable indices 15-22
         (
             [
                 {"role": "system", "content": "You are helpful."},
@@ -158,17 +158,17 @@ def test_validate_chat_template_with_markers(common_tokenizer):
                 29,
                 49152,
             ],
-            [(0, 15), (22, 23)],
+            [(0, 15)],
         ),
-        # User only: no trainable tokens
-        # 9 tokens, no trainable indices
+        # User only: no trainable tokens except EOS
+        # 9 tokens, trainable index 8 (EOS)
         (
             [{"role": "user", "content": "Hi"}],
             [49152, 27, 789, 29, 16946, 750, 789, 29, 49152],
-            [(0, 9)],
+            [(0, 8)],
         ),
         # Long multi-turn (85 tokens, 3 assistant responses with tags, tests span machinery)
-        # Trainable: indices 27-40, 49-62, 70-83
+        # Trainable: indices 27-40, 49-62, 70-84
         (
             [
                 {"role": "system", "content": "You are a helpful assistant that answers questions."},
@@ -266,7 +266,7 @@ def test_validate_chat_template_with_markers(common_tokenizer):
                 29,
                 49152,
             ],
-            [(0, 27), (41, 49), (63, 70), (84, 85)],
+            [(0, 27), (41, 49), (63, 70)],
         ),
     ),
 )